Senior Solutions Architect, AI Factory Observability and Visualization - NVIS

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NVIDIA 's Infrastructure Specialists team is hiring a Senior Solutions Architect - AI Factory Observability Visualization! This remote role develops full-spectrum visibility that supports the smooth functioning of HPC systems and AI factories, transforming intricate telemetry across network and compute into straightforward, actionable perspectives. The role has a complete, end-to-end understanding of the HPC/AI system, running and interpreting microbenchmarks and workloads to confirm system readiness, then establishing the observability that maintains this state. The work involves collaborating across NVIDIA teams to help partners see, understand, and respond to HPC system and AI factory performance, from hardware to workload. What You Will be Doing: Run AI factory validation tools, microbenchmarks, and workloads provided by the team, and interpret results to assess system health and performance. Gain a comprehensive understanding of the system from start to finish, including network topology, interconnects, and compute. Establish what "healthy" represents across the stack — the metrics, logs, and signals that confirm a system is functioning well, and the thresholds that show it isn't. Build and extend the telemetry surface across hardware, fabric, and workload, crafting how data is collected, transformed, stored, and surfaced. Serve as the observability expert, investigating gaps in visibility to ensure it reflects true system behavior. Develop automation (Python, Shell) for collecting, transforming, and presenting system and network data. Recommend improvements to system visibility, data sources, and reporting that give teams clearer insight. Collaborate with hardware, software, networking, datacenter, and product groups to ready HPC systems and AI factories for customer deployment, contributing documentation and readiness materials throughout the process. What We Need to See: Bachelor's degree or equivalent experience in Computer Science, Mathematics, Engineering, Physics, or related field. 6+ years of experience managing Linux-based systems in HPC, distributed systems, or large AI/ML settings. Hands-on experience with the architecture of multi-GPU and/or multi-node clusters, including networking and interconnects. Solid grasp of how HPC and AI factory systems fit together end to end, from network fabric through compute. Proficiency with Python and Shell/Bash for scripting, automation, and tooling. Practical experience working with observability systems (e.g., Prometheus, Grafana, Loki, or similar), including building custom exporters or collectors, setting up alerts, and handling metric cardinality and retention on a large scale. Experience transforming metrics, logs, and traces into clear, actionable insight for complex distributed environments. Familiarity with GPU and fabric telemetry (e.g., DCGM, NVLink, InfiniBand/Ethernet fabric counters) and using it to diagnose performance regressions. Strong communication skills and the ability to work effectively with cross-functional teams. Ways to Stand Out From the Crowd: Experience with AI factory or large-scale AI infrastructure build, deployment, or operations. Background in HPC systems engineering, SRE, or systems analysis for GPU-accelerated environments. Experience building automation and data pipelines that feed dashboards and reporting at scale. Demonstrated desire to use AI to solve practical problems, improve workflows, and guide data-driven decisions. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until June 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an e

NVIDIA 的基础设施专家团队正在招聘一名高级解决方案架构师 - AI 工厂可观测性可视化！该远程职位开发全谱可见性，支持 HPC 系统和 AI 工厂的顺畅运行，将网络和计算中的复杂遥测转化为简单、可操作的视角。该职位需要对 HPC/AI 系统有完整的端到端理解，运行和解读微基准测试和工作负载以确认系统就绪状态，然后建立维持此状态的可观测性。工作涉及与 NVIDIA 各团队协作，帮助合作伙伴查看、理解并响应 HPC 系统和 AI 工厂性能，从硬件到工作负载。您将要做的工作：运行团队提供的 AI 工厂验证工具、微基准测试和工作负载，并解读结果以评估系统健康状况和性能。全面理解系统从开始到结束的各个环节，包括网络拓扑、互连和计算。确立整个堆栈中“健康”代表什么——确认系统运行良好的指标、日志和信号，以及表明系统运行不佳的阈值。构建并扩展跨硬件、Fabric 和工作负载的遥测面，精心设计数据的收集、转换、存储和呈现方式。作为可观测性专家，调查可见性缺口以确保其反映真实的系统行为。开发自动化（Python、Shell）用于收集、转换和呈现系统与网络数据。建议改进系统可见性、数据源和报告，为团队提供更清晰的洞察。与硬件、软件、网络、数据中心和产品团队协作，使 HPC 系统和 AI 工厂做好客户部署准备，并在整个过程中贡献文档和就绪材料。我们需要看到的：计算机科学、数学、工程、物理或相关领域的学士学位或同等经验。6 年以上在 HPC、分布式系统或大型 AI/ML 环境中管理基于 Linux 系统的经验。具有多 GPU 和/或多节点集群架构的实践经验，包括网络和互连。对 HPC 和 AI 工厂系统从网络 Fabric 到计算的端到端组合方式有扎实理解。熟练使用 Python 和 Shell/Bash 进行脚本编写、自动化和工具开发。具有可观测性系统（例如 Prometheus、Grafana、Loki 或类似系统）的实践经验，包括构建自定义 exporter 或 collector、设置告警，以及在大规模下处理指标基数和保留。具有将指标、日志和追踪转化为复杂分布式环境的清晰、可操作洞察的经验。熟悉 GPU 和 Fabric 遥测（例如 DCGM、NVLink、InfiniBand/Ethernet Fabric 计数器），并利用其诊断性能回归。出色的沟通能力以及与跨职能团队有效合作的能力。脱颖而出的方式：具有 AI 工厂或大规模 AI 基础设施构建、部署或运营经验。具有 HPC 系统工程、SRE 或 GPU 加速环境系统分析背景。具有构建自动化和数据管道的经验，为大规模仪表板和报告提供数据。展现出利用 AI 解决实际问题、改进工作流程并指导数据驱动决策的意愿。您的 base salary 将根据您的地点、经验以及类似职位员工的薪酬确定。Level 4 的 base salary 范围为 184,000 USD - 287,500 USD，Level 5 为 224,000 USD - 356,500 USD。您还将有资格获得股权和福利。该职位的申请将至少接受至 2026 年 6 月 28 日。此发布针对现有空缺。NVIDIA 在其招聘流程中使用 AI 工具。NVIDIA 致力于营造包容的工作环境，并自豪地成为 e

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